Individual-based Method Research Articles

Acute limbic system connectivity predicts chronic cognitive function in mild traumatic brain injury: An individualized differential structural covariance network study

Mild traumatic brain injury (mTBI) is a known risk factor for neurodegenerative diseases, yet the precise pathophysiological mechanisms remain poorly understand, often obscured by group-level analysis in non-invasive neuroimaging studies. Individual-based method is critical to exploring heterogeneity in mTBI. We recruited 80 mTBI patients and 40 matched healthy controls, obtaining high-resolution structural MRI for constructing Individual Differential Structural Covariance Networks (IDSCN). Comparisons were conducted at both the individual and group levels. Connectome-based Predictive Modeling (CPM) was applied to predict cognitive performance based on whole-brain connectivity. During the acute stage of mTBI, patients exhibited significant heterogeneity in the count and direction of altered edges, obscured by group-level analysis. In the chronic stage, the number of altered edges decreased and became more consistent, aligning with clinical observations of acute cognitive impairment and gradual improvement. Subgroup analysis based on loss of consciousness/post-traumatic amnesia revealed distinct patterns of alterations. The temporal lobe, particularly regions related to the limbic system, significantly predicted cognitive function from acute to chronic stage. The use of IDSCN and CPM has provided valuable individual-level insights, reconciling discrepancies from previous studies. Additionally, the limbic system may be an appropriate target for future intervention efforts.

Evaluating movement-based methods for estimating the frequency and timing of parturition in mule deer

BackgroundInformation on reproduction of harvested species such as mule deer (Odocoileus hemionus) is vital for conservation and management. Furthermore, parturition in ungulates may be detected using patterns of movement logged by GPS transmitters. Several movement-based methods have been developed to detect parturition in ungulates including the Peterson method, behavioral change point analysis (BCPA), rolling minimum convex polygons (rMCP), individual-based method (IBM), and population-based method (PBM). Our objectives were to (1) test the accuracy and the precision of each previously described method and (2) develop an improved method optimized for mule deer that incorporated aspects of the other methods.MethodsWe determined parturition timing and status for female mule deer fitted with GPS collars and implanted with vaginal implant transmitters (VITs). We used movement patterns before and after parturition to set movement thresholds for each movement-based method. Following model training, we used location and birth date data from an external dataset to test the effectiveness of each movement-based method. Additionally, we developed a novel method for detecting parturition called the analysis of parturition indicators (API). We used two regression analyses to determine the accuracy and precision of estimates generated by each method.ResultsThe six methods we employed varied in accuracy, with the API, rMCP, and BCPA being most accurate. Precision also varied among methods, with the API, rMCP, and PBM generating the most precise estimates of parturition dates. The API and the rMCP performed similarly and better overall than any of the other existing methods.ConclusionsWe found that movement-based methods could be used to accurately and precisely detect parturition in mule deer. Further, we determined that the API and rMCP methods had the greatest overall success at detecting parturition in mule deer. The relative success of the API and rMCP may be attributed to the fact that both methods use home range size to detect parturition and are validated using known parturition dates of collared deer. We present the API as an efficient method of estimating birth status and timing of parturition of mule deer fitted with GPS transmitters, as well as affirm the effectiveness of a previously developed method, rMCP.

Decreased Functional and Structural Connectivity is Associated with Core Symptom Improvement in Children with Autism Spectrum Disorder After Mini-basketball Training Program.

Exercise intervention has been proven helpful to ameliorate core symptoms of Autism Spectrum Disorder (ASD). However, the underlying mechanisms are not fully understood. In this study, we carried out a 12-week mini-basketball training program (MBTP) on ASD children and examined the changes of brain functional and structural networks before and after exercise intervention.We applied individual-based method to construct functional network and structural morphological network, and investigated their alterations following MBTP as well as their associations with the change in core symptom. Structural MRI and resting-state functional MRI data were obtained from 58 ASD children aged 3-12 years (experiment group: n = 32, control group: n = 26).ASD children who received MBTP intervention showed several distinguishable alternations compared to the control without special intervention. These included decreased functional connectivity within the sensorimotor network (SM) and between SM and the salience network, decreased morphological connectivity strength in a cortical-cortical network centered on the left inferior temporal gyrus, and a subcortical-cortical network centered on the left caudate. Particularly, the aforementioned functional and structural changes induced by MBTP were associated with core symptoms of ASD.Our findings suggested that MBTP intervention could be an effective approach to improve core symptoms in ASD children, decrease connectivity in both structure and function networks, and may drive the brain change towards normal-like neuroanatomy.

A Method to Select Plus Tree for Flower Purpose in Forestry

Plus tree selection is the first step to improve production and quality in forestry. An individual-based method is widely used to select plus trees for timber production, timber form, freedom from diseases and insects. In this study, a method to select plus trees for flower production is described and named as a crown-area-based method. Both individual-based and crown-area-based methods were used to select plus trees for Camellia impressinervis, a golden camellia; its yellow flowers have been used to treat sore throat and diarrhea, and to prevent cancers in China and Vietnam. Flower production of 21 concerned individuals was compared to the population mean and it was generated as a percentage. The population mean of the individual-based method is the mean of production of 21 trees as mean production/tree. While population mean of the crown-area-based method is mean production/m2 crown area (first production/m2 crown area for each tree was generated, then mean for population). The results indicated that both methods show seven individual trees with flower production >100% population mean. However, individual trees are different. Only five of 7 trees are the same in both methods. The tree rankings by flower production percentage in both methods are totally different. The highest ranking by individual-based method (310% mean) is 4th ranking by crown-area-based method (181% mean). While the highest ranking by crown-area-based method (270% mean) is third ranking by individual-based method (260% mean). It is concluded that crown-area-based method is better in selecting plus trees for flower purpose, as it considers the crown area which is known as a productive part of a tree to form flowers.

Implementing a novel movement-based approach to inferring parturition and neonate caribou calf survival.

In ungulates, parturition is correlated with a reduction in movement rate. With advances in movement-based technologies comes an opportunity to develop new techniques to assess reproduction in wild ungulates that are less invasive and reduce biases. DeMars et al. (2013, Ecology and Evolution 3:4149–4160) proposed two promising new methods (individual- and population-based; the DeMars model) that use GPS inter-fix step length of adult female caribou (Rangifer tarandus caribou) to infer parturition and neonate survival. Our objective was to apply the DeMars model to caribou populations that may violate model assumptions for retrospective analysis of parturition and calf survival. We extended the use of the DeMars model after assigning parturition and calf mortality status by examining herd-wide distributions of parturition date, calf mortality date, and survival. We used the DeMars model to estimate parturition and calf mortality events and compared them with the known parturition and calf mortality events from collared adult females (n = 19). We also used the DeMars model to estimate parturition and calf mortality events for collared female caribou with unknown parturition and calf mortality events (n = 43) and instead derived herd-wide estimates of calf survival as well as distributions of parturition and calf mortality dates and compared them to herd-wide estimates generated from calves fitted with VHF collars (n = 134). For our data, the individual-based method was effective at predicting calf mortality, but was not effective at predicting parturition. The population-based method was more effective at predicting parturition but was not effective at predicting calf mortality. At the herd-level, the predicted distributions of parturition date from both methods differed from each other and from the distribution derived from the parturition dates of VHF-collared calves (log-ranked test: χ2 = 40.5, df = 2, p < 0.01). The predicted distributions of calf mortality dates from both methods were similar to the observed distribution derived from VHF-collared calves. Both methods underestimated herd-wide calf survival based on VHF-collared calves, however, a combination of the individual- and population-based methods produced herd-wide survival estimates similar to estimates generated from collared calves. The limitations we experienced when applying the DeMars model could result from the shortcomings in our data violating model assumptions. However despite the differences in our caribou systems, with proper validation techniques the framework in the DeMars model is sufficient to make inferences on parturition and calf mortality.

Linking GPS Telemetry Surveys and Scat Analyses Helps Explain Variability in Black Bear Foraging Strategies

Studying diet is fundamental to animal ecology and scat analysis, a widespread approach, is considered a reliable dietary proxy. Nonetheless, this method has weaknesses such as non-random sampling of habitats and individuals, inaccurate evaluation of excretion date, and lack of assessment of inter-individual dietary variability. We coupled GPS telemetry and scat analyses of black bears Ursus americanus Pallas to relate diet to individual characteristics and habitat use patterns while foraging. We captured 20 black bears (6 males and 14 females) and fitted them with GPS/Argos collars. We then surveyed GPS locations shortly after individual bear visits and collected 139 feces in 71 different locations. Fecal content (relative dry matter biomass of ingested items) was subsequently linked to individual characteristics (sex, age, reproductive status) and to habitats visited during foraging bouts using Brownian bridges based on GPS locations prior to feces excretion. At the population level, diet composition was similar to what was previously described in studies on black bears. However, our individual-based method allowed us to highlight different intra-population patterns, showing that sex and female reproductive status had significant influence on individual diet. For example, in the same habitats, females with cubs did not use the same food sources as lone bears. Linking fecal content (i.e., food sources) to habitat previously visited by different individuals, we demonstrated a potential differential use of similar habitats dependent on individual characteristics. Females with cubs-of-the-year tended to use old forest clearcuts (6–20 years old) to feed on bunchberry, whereas females with yearling foraged for blueberry and lone bears for ants. Coupling GPS telemetry and scat analyses allows for efficient detection of inter-individual or inter-group variations in foraging strategies and of linkages between previous habitat use and food consumption, even for cryptic species. This approach could have interesting ecological implications, such as supporting the identification of habitats types abundant in important food sources for endangered species targeted by conservation measures or for management actions for depredating animals.

How much of the storage in the ecosystem is due to cycling?

Cycling is the process of reutilization of matter or energy in the ecosystem. As it is not directly measurable, the strength of cycling is calculated based on mathematical models of the ecosystem. For a storage-flow type ecosystem model, throughflow is the total amount of material flowing through all system compartments per unit of time, while storage represents the total standing stock in the system. Finn׳s cycling index (FCI) is widely used to measure the cycled throughflow, the proportion of throughflow generated by cycling. Thus, although originally named after its author J.T. Finn, FCI can also be called a “flow-based” cycling index. In addition to flow, storage plays an important role in generating network properties, and therefore should be taken into account in measuring cycling. In this paper, we investigate how much of the total standing stock of matter or energy in the ecosystem is due to cycling, and formulate a storage-based cycling index (SCI), by utilizing an individual-based method to simulate the system. SCI utilizes flow values used for FCI and takes into account residence time as well. Therefore, SCI is a preferable index for quantifying cycling in ecosystems.

Optimising resources and management of genetic variation in fish-breeding schemes with multiple traits

When setting up a breeding program for fish, an optimal breeding scheme is sought, and especially the number of families to use is a pivot parameter in this regard. This simulation study tests a range of probable number of families, with the use of two different methods for implementation of optimum contribution procedures in fish: one based on individual quotas and one with family quotas. Schemes are compared at the same prescribed rate of inbreeding. The breeding goal consisted of two correlated traits, one that could be measured on all selection candidates, the second only on full-sibs. The number of families ranged from 50 to 400, whereas the number of offspring per full-sib family was fixed at 50. Average genetic gain for generations 5 to 15 was used for comparing the schemes, and the rate of inbreeding per generation was restricted to 1%. The individual-based method gave the overall highest genetic gain, but the superiority for this method was most evident for the breeding schemes with a high number of families. The biggest difference between the two methods tested stems from the fact that the family-based method furnished a relatively larger proportion of the gain on the first trait; measurable only on the informants. For the individual-based method, this trait had negative or almost no gain when the genetic correlation was negative. The study also showed that although the total gain did not differ too much, the choice of method could highly influence the specific gain in each of the two traits. It is concluded that for the parameters and assumptions used in this study, the optimal number of families for both methods are likely to be around 200 to 300 if economic considerations are also included.

Inferring parturition and neonate survival from movement patterns of female ungulates: a case study using woodland caribou

Analyses of animal movement data have primarily focused on understanding patterns of space use and the behavioural processes driving them. Here, we analyzed animal movement data to infer components of individual fitness, specifically parturition and neonate survival. We predicted that parturition and neonate loss events could be identified by sudden and marked changes in female movement patterns. Using GPS radio-telemetry data from female woodland caribou (Rangifer tarandus caribou), we developed and tested two novel movement-based methods for inferring parturition and neonate survival. The first method estimated movement thresholds indicative of parturition and neonate loss from population-level data then applied these thresholds in a moving-window analysis on individual time-series data. The second method used an individual-based approach that discriminated among three a priori models representing the movement patterns of non-parturient females, females with surviving offspring, and females losing offspring. The models assumed that step lengths (the distance between successive GPS locations) were exponentially distributed and that abrupt changes in the scale parameter of the exponential distribution were indicative of parturition and offspring loss. Both methods predicted parturition with near certainty (>97% accuracy) and produced appropriate predictions of parturition dates. Prediction of neonate survival was affected by data quality for both methods; however, when using high quality data (i.e., with few missing GPS locations), the individual-based method performed better, predicting neonate survival status with an accuracy rate of 87%. Understanding ungulate population dynamics often requires estimates of parturition and neonate survival rates. With GPS radio-collars increasingly being used in research and management of ungulates, our movement-based methods represent a viable approach for estimating rates of both parameters.

Spatial Genetic Analyses Reveal Cryptic Population Structure and Migration Patterns in a Continuously Harvested Grey Wolf (Canis lupus) Population in North-Eastern Europe

Spatial genetics is a relatively new field in wildlife and conservation biology that is becoming an essential tool for unravelling the complexities of animal population processes, and for designing effective strategies for conservation and management. Conceptual and methodological developments in this field are therefore critical. Here we present two novel methodological approaches that further the analytical possibilities of STRUCTURE and DResD. Using these approaches we analyse structure and migrations in a grey wolf ( Canis lupus ) population in north-eastern Europe. We genotyped 16 microsatellite loci in 166 individuals sampled from the wolf population in Estonia and Latvia that has been under strong and continuous hunting pressure for decades. Our analysis demonstrated that this relatively small wolf population is represented by four genetic groups. We also used a novel methodological approach that uses linear interpolation to statistically test the spatial separation of genetic groups. The new method, which is capable of using program STRUCTURE output, can be applied widely in population genetics to reveal both core areas and areas of low significance for genetic groups. We also used a recently developed spatially explicit individual-based method DResD, and applied it for the first time to microsatellite data, revealing a migration corridor and barriers, and several contact zones.

Assessment of biases in the estimation of tag shedding rates through a mark-resight experiment

Several flexible methods for estimating tag loss rates through mark-resight data have been developed recently. They allow evaluation of different tag shedding modalities and relax the usual assumption of independence between the loss of tags made in classical double-tagging methods. Two conditions limit the applicability of these methods: (1) tagged individuals must have permanent marks so that they can still be identified after losing their tags, and (2) a large number of observations is required to obtain precise estimates. Here we evaluate the performance of alternative estimators of tag shedding rates when these conditions are not met, a situation that is very common in mark-resight experiments on reef fishes. We simulated resighting data using a simple exponential model of tag shedding under different scenarios created by varying the probabilities of fish detection and fish emigration from the reef, and the tagging schedule. The model was conditioned on actual data from a short-term (∼1.5 years) double-tagging study conducted on the Argentine sandperch Pseudopercis semifasciata (Cuvier 1829) in rocky reefs of northern Patagonia. We tested eight estimation procedures: three variants of an individual-based method, two based on a binomial likelihood function for exact or pooled times-at-liberty data, and three regression methods. Although the individual-based approach produced unbiased and most precise estimates when individuals that had lost both tags were identifiable, it performed poorly in the absence of permanent tags. In contrast, conditional methods, which do not require identification of individuals that have lost both tags, were more robust, providing unbiased and precise estimates. The pros and cons of the different methods for analyzing small-scale mark-resight experiments are discussed.

Low genetic and morphological differentiation between an introduced population of dunnocks in New Zealand and an ancestral population in England

Species invasions and exotic species introductions can be considered as ‘unplanned experiments’, which help us to understand the evolution of organisms. In this study, we investigated whether an exotic bird species, the dunnock (Prunella modularis), has diverged genetically and morphologically from its native source population (Cambridge, England) after introduction into a new environment (Dunedin, South Island of New Zealand; exotic population). We used a set of microsatellite markers and three morphological traits to quantify the divergence between these two populations. We quantified neutral genotypic differentiation between the populations, and also used an individual-based Bayesian clustering method to assess genetic structure. We compared morphological divergence using univariate and principal components analyses. We found that individuals from the Dunedin population are genetically distinct from the Cambridge population, but levels of differentiation are very low. Overall within-population levels of genetic diversity are low compared to other bird species, and effective population sizes are small; indicating that the native population probably has a historically low level of genetic diversity, and that the introduced population retained most of that diversity after its introduction into New Zealand. We found little evidence of morphological divergence, and the evolutionary rate of change in these traits is below the average for other taxa. Our study adds support to the growing literature showing that invasive species maintain most of their initial genetic diversity after multiple founder events, even when population size is severely reduced. Moreover, our morphological data indicate slow evolutionary rates in species introduced to similar habitats.

Using movement behaviour to define biological seasons for woodland caribou

Terrestrial mammals are strongly influenced by seasonal changes in environmental conditions. Studies of animal space use behaviour are therefore inherently seasonal in nature. We propose an individual-based quantitative method for identifying seasonal shifts in caribou movement behaviour and we demonstrate its use in determining the onset of the winter, spring dispersal, and calving seasons. Using pooled data for the population we demonstrate an alternate approach using polynomial regression with mixed effects. We then compare individual onset dates with population-based estimates and those adopted by expert consensus for our study area. Distributions of individual-based onset dates were normally distributed with prominent modes; however, there was considerable variation in individual onset times. Population-based estimates were closer to the peaks of individual estimates than were expert-based estimates, which fell outside the onetailed 90% and 95% sample quantiles of individually-fitted distributions for spring and winter, respectively. Both expertand population-based estimates were later for winter and earlier for both spring and calving than were individual-based estimates. We discuss the potential consequences of neglecting to corroborate conventionally used dates with observed seasonal trends in movement behaviour. In closing, we recommend researchers adopt an individual-based quantitative approach and a variable temporal window for data set extraction.

Atlas‐Based Versus Individual‐Based Fiber Tracking of the Corpus Callosum in Patients with Multiple Sclerosis: Reliability and Clinical Correlations

In multiple sclerosis (MS), the presence of lesions and normal-appearing white matter damage may affect the reliability of diffusion tensor (DT) magnetic resonance imaging (MRI)-based tractography. We compared the performance of an individual-based method for corpus callosum (CC) fiber tracking in MS with those of two atlas-based methods. Brain DT MRI scans were acquired from 35 patients with MS and 18 age-matched healthy volunteers (HV). DT-derived metrics from the CC-the mean diffusivity (MD) and fractional anisotropy (FA)-were calculated using an individual-based and two atlas-based methods with different types of subject registration (linear and nonlinear) to a CC atlas. Customized termination criteria were applied to stop the tracking algorithm when using the individual-based method. All the methods were able to distinguish between MS patients and HV. Using the individual-based method, stronger relationships were found between CC DT-derived metrics and the subjects' clinical condition. CC DT tractography using an individual-based method is more sensitive than the atlas-based ones to tract-specific alterations related to MS disability. An atlas-based method with nonlinear registration can be a valid alternative when an automated postprocessing is warranted, such as in the case of high volumes of data.

Cross-lingual text categorization: Conquering language boundaries in globalized environments

Text categorization pertains to the automatic learning of a text categorization model from a training set of preclassified documents on the basis of their contents and the subsequent assignment of unclassified documents to appropriate categories. Most existing text categorization techniques deal with monolingual documents (i.e., written in the same language) during the learning of the text categorization model and category assignment (or prediction) for unclassified documents. However, with the globalization of business environments and advances in Internet technology, an organization or individual may generate and organize into categories documents in one language and subsequently archive documents in different languages into existing categories, which necessitate cross-lingual text categorization (CLTC). Specifically, cross-lingual text categorization deals with learning a text categorization model from a set of training documents written in one language (e.g., L 1) and then classifying new documents in a different language (e.g., L 2). Motivated by the significance of this demand, this study aims to design a CLTC technique with two different category assignment methods, namely, individual- and cluster-based. Using monolingual text categorization as a performance reference, our empirical evaluation results demonstrate the cross-lingual capability of the proposed CLTC technique. Moreover, the classification accuracy achieved by the cluster-based category assignment method is statistically significantly higher than that attained by the individual-based method.

Accounting for Individuals, Uncertainty, and Multiscale Clustering in Core Area Estimation

Core areas are important descriptors of animal space-use patterns, but current estimation methods rely on arbitrary rules and potentially lead to imprecise or erroneous area estimates. We proposed a Bayesian statistical model that incorporates an individual-based method for estimating core area boundaries. The model accounts for boundary uncertainty and multiple scales of clustering by partitioning a home range into ≥2 completely spatially random point patterns defined by a kernel density isopleth. We used data from coyotes (Canis latrans), bobcats (Lynx rufus), and red-shouldered hawks (Buteo lineatus) to estimate core areas for individual animals. We also estimated core areas from simulated point patterns with known boundaries, varying numbers of points, and relative densities of points inside core areas, and compared estimates to those obtained using the 50% isopleth. Optimal isopleths for the empirical data ranged between 18.7% and 71.5%. We found no species-specific range of core area isopleths. Across all simulated scenarios, our method outperformed the 50% isopleth-based estimate, which consistently overestimated core areas. Minta overlap values were 20–40% higher across all scenarios for our method compared to the 50% isopleth. Minta overlap values were >75% in 90% of scenarios using our method. Objectively estimating core areas using our individual-based method may lead to improved inference about which behavioral and ecological processes underlie observed space-use patterns because of greater estimate precision.

Estimating CD4+ Cell Counts of an Individual using Population Historical Data

+ cell count; Total lymphocyte count; Sample-based prediction method; Individual-based prediction method; Sensitivity; Predictive-positive rate Abstract Background and objective: WHO guidelines in 2010 no longer recommend the total lymphocyte count (TLC), instead of the CD4 + cell (CD4) count, in deciding on the initiation of anti-retroviral treatment. This is very problematic because of the cost and resources involved in getting CD4 counts. To solve this problem, we developed an efficient and reliable method for predicting CD4 counts based on a previous CD4 count. Subjects and methods: To surmount the degrading of the precision due to the individual variability in CD4 counts, we developed an individual-based prediction method. Results: The sensitivity and the predictive-positive rate of CD4 counts below 350 cells/mm 3 were 89% and 88%, respectively, at a one-month interval and 76% and 84%, respectively, at a six-month interval. Conclusion: The individual-based prediction method of the CD4 count will be useful and critical in resource-poor regions where CD4 counts are not repeatedly available.

When dispersal fails: unexpected genetic separation in Gibraltar macaques (Macaca sylvanus)

Barbary macaques (Macaca sylvanus), now restricted in the wild to a few isolated forested areas of Morocco and Algeria, are present in a free-ranging colony on Gibraltar. For many decades, the Gibraltar colony was exposed to multiple bottlenecks due to highly nonrandom removal of animals, followed by repeated introductions of animals from North Africa. Moreover, because of complete isolation, Gibraltar's several social groups of macaques provide an ideal system to study the genetic consequences of dispersal in cercopithecines in situ. Predictions of genetic consequences due to male-biased dispersal in cercopithecines will be different for autosomal and maternally inherited genetic markers, such as the control region of the mitochondrial DNA. We used a panel of 14 highly polymorphic microsatellite loci and part of the hypervariable region I of the mitochondrial control region to estimate genetic structure between five social groups in Gibraltar. Surprisingly, for autosomal markers, both classical summary statistics and an individual-based method using a Bayesian framework detected significant genetic structure between social groups in Gibraltar, despite much closer proximity than wild Algerian and Moroccan populations. Mitochondrial data support this finding, as a very substantial portion of the total genetic variation (70.2%) was found between social groups. Using two Bayesian approaches, we likewise identified not only a small number of male first-generation immigrants (albeit less than expected for cercopithecines) but also unexpectedly a few females. We hypothesize that the culling of males that are more likely to disperse might slow down genetic homogenization among neighbouring groups, but may also and more perversely produce selection on certain behavioural traits. This may have important repercussions for conservation, as it could lead to evolutionary changes that are not due to inbreeding or genetic drift.

An Individual-Based Method to Measure Animal Activity Levels: A Test on Brown Bears

Measuring activity levels in animals provides important information about their behavioral ecology and may be a relevant factor in management and conservation. We tested an individual-based method to discriminate active and passive behaviors on brown bears (Ursus arctos), using a dual-axis motion sensor mounted on Global Positioning System-Global System for Mobile Communications (GPS-GSM) collars. The method takes into account individual variation in activity levels and does not require further calibration. We validated the method through direct observations of captive bears and an extensive survey of wild bear signs in the boreal forest of central Sweden. We found good correspondence between sensor-measured and observed activity on captive bears. Analysis of wild bear signs at GPS locations and its comparison with the collar-based activity status confirmed the possibility of successfully applying the method to study brown bear activity patterns in the wild. The method provided 94.3% correct activity classification on captive bears and about 78.2% on wild bears. We tested the possibility of using this technique to measure increasing levels of activity by analyzing the correlation between the collar-derived numeric activity and the intensity of bear movement. At a broader scale (active vs. passive), the sensor-measured value provided information on the degree of activity, but no correlation was evident at a finer scale (specific behaviors). We suggest that using more sensors in different regions of a bear's body could overcome this difficulty and improve our knowledge of animal behavior in the wild, through remote monitoring of activity levels. We conclude that this method can be useful in the study of behavioral ecology of a wide range of animals, especially species that are difficult to observe or move great distances.

Modeling of the Oncorhynchus nerka Population of Dal'neye Lake (Kamchatka) Applying an Individual-Based Method

A computer model of the sockeye salmon (Onchorhynchus nerka) population from Dal'neye Lake (Kamchatka) based on the results of long-term research was developed. As opposed to an earlier published model [4], the stochastic approach and individual-based method were used in the present model. The application of such techniques in the model has enabled study of the dynamics of the genetic structure of the population under the effect of varying environments, both in the sea and in the fresh-water period of the sockeye's life, and discovery of patterns of transition from the cyclic fluctuation mode to the mode of chaotic change of number.